Python package which accelerates OpenCV image filtering functions for the PYNQ framework
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Wolfgang Brueckner
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README.md

cv2PYNQ

This Python package accelerates OpenCV image filtering functions for the PYNQ platform. The library implements a specific set of popular image filters and feature detection algorithms. The calculation of time-consuming tasks is implemented in the Programmable Logic (PL) of the ZYNQ chip. cv2PYNQ also includes the Video-Subsystem of the base project of PYNQ. Therefore, the HDMI In and Out interfaces can be used in your application. The library calculates every filter for gray-channel images with 1080p within 16 ms if the input and output buffers are located in the contiguous memory of the chip.

Get Started

Install by typing:

git clone https://github.com/wbrueckner/cv2pynq.git   
cd cv2pynq/   
pip3.6 install -e .   

into the terminal on your Pynq-Z1 board.
The library comes with a jupyter notebook to demonstrate its usage and capabilities. You find the notebook in the cv2PYNQ folder of your home tree after installation.

Link to YouTube Video: https://www.youtube.com/watch?v=nRxe-NqvOl8

Currently accelerated functions:

  • Sobel: 3x3; 5x5
  • Scharr
  • Laplacian: ksize = 1; 3; 5
  • blur: ksize = 3
  • GaussinBlur: ksize = 3
  • erode: ksize = 3
  • dilate: ksize = 3
  • Canny

Contribute to cv2PYNQ

Read the instructions in cv2PYNQ - The project behind the library.